Professionalisation of sport federations - a multi-level framework for analysing forms, causes and consequences

Research question: International and national sport federations as well as their member organisations are key actors within the sport system and have a wide range of relationships outside the sport system (e.g. with the state, sponsors, and the media). They are currently facing major challenges such as growing competition in top-level sports, democratisation of sports with 'sports for all' and sports as the answer to social problems. In this context, professionalising sport organisations seems to be an appropriate strategy to face these challenges and current problems. We define the professionalisation of sport organisations as an organisational process of transformation leading towards organisational rationalisation, efficiency and business-like management. This has led to a profound organisational change, particularly within sport federations, characterised by the strengthening of institutional management (managerialism) and the implementation of efficiency-based management instruments and paid staff. Research methods: The goal of this article is to review the current international literature and establish a global understanding of and theoretical framework for analysing why and how sport organisations professionalise and what consequences this may have. Results and findings: Our multi-level approach based on the social theory of action integrates the current concepts for analysing professionalisation in sport federations. We specify the framework for the following research perspectives: (1) forms, (2) causes and (3) consequences, and discuss the reciprocal relations between sport federations and their member organisations in this context. Implications: Finally, we work out a research agenda and derive general methodological consequences for the investigation of professionalisation processes in sport organisations.

Very high-resolution digital elevation models: are multi-scale-derived variables ecologically relevant?

1. Digital elevation models (DEMs) are often used in landscape ecology to retrieve elevation or first derivative terrain attributes such as slope or aspect in the context of species distribution modelling. However, DEM-derived variables are scale-dependent and, given the increasing availability of very high-resolution (VHR) DEMs, their ecological relevancemust be assessed for different spatial resolutions. 2. In a study area located in the Swiss Western Alps, we computed VHR DEMs-derived variables related to morphometry, hydrology and solar radiation. Based on an original spatial resolution of 0.5 m, we generated DEM-derived variables at 1, 2 and 4 mspatial resolutions, applying a Gaussian Pyramid. Their associations with local climatic factors, measured by sensors (direct and ambient air temperature, air humidity and soil moisture) as well as ecological indicators derived fromspecies composition, were assessed with multivariate generalized linearmodels (GLM) andmixed models (GLMM). 3. Specific VHR DEM-derived variables showed significant associations with climatic factors. In addition to slope, aspect and curvature, the underused wetness and ruggedness indices modelledmeasured ambient humidity and soilmoisture, respectively. Remarkably, spatial resolution of VHR DEM-derived variables had a significant influence on models' strength, with coefficients of determination decreasing with coarser resolutions or showing a local optimumwith a 2 mresolution, depending on the variable considered. 4. These results support the relevance of using multi-scale DEM variables to provide surrogates for important climatic variables such as humidity, moisture and temperature, offering suitable alternatives to direct measurements for evolutionary ecology studies at a local scale.

Classification supervisée multi-étiquette en actes de dialogue: analyse discriminante et transformations de Schoenberg

Abstract This work studies the multi-label classification of turns in simple English Wikipedia talk pages into dialog acts. The treated dataset was created and multi-labeled by (Ferschke et al., 2012). The first part analyses dependences between labels, in order to examine the annotation coherence and to determine a classification method. Then, a multi-label classification is computed, after transforming the problem into binary relevance. Regarding features, whereas (Ferschke et al., 2012) use features such as uni-, bi-, and trigrams, time distance between turns or the indentation level of the turn, other features are considered here: lemmas, part-of-speech tags and the meaning of verbs (according to WordNet). The dataset authors applied approaches such as Naive Bayes or Support Vector Machines. The present paper proposes, as an alternative, to use Schoenberg transformations which, following the example of kernel methods, transform original Euclidean distances into other Euclidean distances, in a space of high dimensionality. Résumé Ce travail étudie la classification supervisée multi-étiquette en actes de dialogue des tours de parole des contributeurs aux pages de discussion de Simple English Wikipedia (Wikipédia en anglais simple). Le jeu de données considéré a été créé et multi-étiqueté par (Ferschke et al., 2012). Une première partie analyse les relations entre les étiquettes pour examiner la cohérence des annotations et pour déterminer une méthode de classification. Ensuite, une classification supervisée multi-étiquette est effectuée, après recodage binaire des étiquettes. Concernant les variables, alors que (Ferschke et al., 2012) utilisent des caractéristiques telles que les uni-, bi- et trigrammes, le temps entre les tours de parole ou l'indentation d'un tour de parole, d'autres descripteurs sont considérés ici : les lemmes, les catégories morphosyntaxiques et le sens des verbes (selon WordNet). Les auteurs du jeu de données ont employé des approches telles que le Naive Bayes ou les Séparateurs à Vastes Marges (SVM) pour la classification. Cet article propose, de façon alternative, d'utiliser et d'étendre l'analyse discriminante linéaire aux transformations de Schoenberg qui, à l'instar des méthodes à noyau, transforment les distances euclidiennes originales en d'autres distances euclidiennes, dans un espace de haute dimensionnalité.

Gamma oscillations in V1 are correlated with GABAA receptor density: A multi-modal MEG and Flumazenil-PET study.

High-frequency oscillations in the gamma-band reflect rhythmic synchronization of spike timing in active neural networks. The modulation of gamma oscillations is a widely established mechanism in a variety of neurobiological processes, yet its neurochemical basis is not fully understood. Modeling, in-vitro and in-vivo animal studies suggest that gamma oscillation properties depend on GABAergic inhibition. In humans, search for evidence linking total GABA concentration to gamma oscillations has led to promising -but also to partly diverging- observations. Here, we provide the first evidence of a direct relationship between the density of GABAA receptors and gamma oscillatory gamma responses in human primary visual cortex (V1). By combining Flumazenil-PET (to measure resting-levels of GABAA receptor density) and MEG (to measure visually-induced gamma oscillations), we found that GABAA receptor densities correlated positively with the frequency and negatively with amplitude of visually-induced gamma oscillations in V1. Our findings demonstrate that gamma-band response profiles of primary visual cortex across healthy individuals are shaped by GABAA-receptor-mediated inhibitory neurotransmission. These results bridge the gap with in-vitro and animal studies and may have future clinical implications given that altered GABAergic function, including dysregulation of GABAA receptors, has been related to psychiatric disorders including schizophrenia and depression.

Automatic Brain Extraction in Fetal MRI using Multi-Atlas-based Segmentation

In fetal brain MRI, most of the high-resolution reconstruction algorithms rely on brain segmentation as a preprocessing step. Manual brain segmentation is however highly time-consuming and therefore not a realistic solution. In this work, we assess on a large dataset the performance of Multiple Atlas Fusion (MAF) strategies to automatically address this problem. Firstly, we show that MAF significantly increase the accuracy of brain segmentation as regards single-atlas strategy. Secondly, we show that MAF compares favorably with the most recent approach (Dice above 0.90). Finally, we show that MAF could in turn provide an enhancement in terms of reconstruction quality.

Fast and sensitive supercritical fluid chromatography - tandem mass spectrometry multi-class screening method for the determination of doping agents in urine.

This study shows the possibility offered by modern ultra-high performance supercritical fluid chromatography combined with tandem mass spectrometry in doping control analysis. A high throughput screening method was developed for 100 substances belonging to the challenging classes of anabolic agents, hormones and metabolic modulators, synthetic cannabinoids and glucocorticoids, which should be detected at low concentrations in urine. To selectively extract these doping agents from urine, a supported liquid extraction procedure was implemented in a 48-well plate format. At the tested concentration levels ranging from 0.5 to 5 ng/mL, the recoveries were better than 70% for 48-68% of the compounds and higher than 50% for 83-87% of the tested substances. Due to the numerous interferences related to isomers of steroids and ions produced by the loss of water in the electrospray source, the choice of SFC separation conditions was very challenging. After careful optimization, a Diol stationary phase was employed. The total analysis time for the screening assay was only 8 min, and interferences as well as susceptibility to matrix effect (ME) were minimized. With the developed method, about 70% of the compounds had relative ME within the range ±20%, at a concentration of 1 and 5 ng/mL. Finally, limits of detection achieved with the above-described strategy including 5-fold preconcentration were below 0.1 ng/mL for the majority of the tested compounds. Therefore, LODs were systematically better than the minimum required performance levels established by the World anti-doping agency, except for very few metabolites.